What are the open source cloud computing platforms?
The open source cloud computing platforms include: 1. AbiCloud enterprise-level open source cloud computing platform; 2. Eucalyptus open source cloud computing platform; 3. 10gen MongoDB open source high-performance storage platform; 4. Enomalism elastic computing platform; 5. Nimbus cloud computing platform.
Sharing of five open source computing platforms:
(Recommended graphic tutorial: Getting started with java)
1. AbiCloud enterprise-level open source cloud computing platform
Abiquo company launched an open source cloud computing platform - "abiCloud", which enables companies to create and manage large-scale cloud computing platforms in a fast, simple and scalable way. , Complex IT infrastructure (including virtual servers, networks, applications, storage devices, etc.). One of the main differences between AbiCloud and other similar products is its powerful web interface management. You can deploy a new service by dragging and dropping a virtual machine. This version allows instances to be deployed via VirtualBox, which also supports VMware, KVM and Xen.
2. Eucalyptus Open Source Cloud Computing Platform
The Eucalyptus project (Elastic Utility Computing Architecture for Linking Your Programs To Useful Systems) is an open source implementation of Amazon EC2 that is compatible with commercial service interfaces. Like EC2, Eucalyptus relies on Linux and Xen for operating system virtualization. Eucalyptus was developed at the University of California (Santa Barbara) for cloud computing research. You can download it from the university's website or try it through the Eucalyptus Public Cloud, although the latter has some limitations.
3. 10gen MongoDB open source high-performance storage platform
10gen is both a cloud platform and a downloadable open source package that can be used to create your own private cloud. 10gen is a software stack similar to App Engine that provides similar functionality to App Engine — but with a few differences. With 10gen, applications can be developed using Python as well as JavaScript and Ruby programming languages. The platform also uses the concept of sandboxing to isolate applications and provide a reliable environment using many computers (built on Linux, of course) with their own application servers.
4. Enomalism Elastic Computing Platform
Enomaly's Elastic Computing Platform (ECP) is a programmable virtual cloud architecture. The ECP platform can simplify the operation of publishing applications in the cloud architecture.
The cloud computing platform is an EC2 style IaaS. Enomalism is an open source project that provides a cloud computing framework with functionality similar to EC2. Enomalism is based on Linux and supports both Xen and Kernel Virtual Machine (KVM). Unlike other pure IaaS solutions, Enomalism provides a software stack based on the TurboGears web application framework and Python.
5. Cloud computing platform Nimbus
Nimbus is provided by the grid middleware Globus and evolved from Virtual Workspace. Like Eucalyptus, it provides similar functions and interfaces to EC2.
Related recommendations: php training
The above is the detailed content of What are the open source cloud computing platforms?. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
AI Hentai Generator
Generate AI Hentai for free.
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
15 recommended open source free image annotation tools
Mar 28, 2024 pm 01:21 PM
Image annotation is the process of associating labels or descriptive information with images to give deeper meaning and explanation to the image content. This process is critical to machine learning, which helps train vision models to more accurately identify individual elements in images. By adding annotations to images, the computer can understand the semantics and context behind the images, thereby improving the ability to understand and analyze the image content. Image annotation has a wide range of applications, covering many fields, such as computer vision, natural language processing, and graph vision models. It has a wide range of applications, such as assisting vehicles in identifying obstacles on the road, and helping in the detection and diagnosis of diseases through medical image recognition. . This article mainly recommends some better open source and free image annotation tools. 1.Makesens
Ten recommended open source free text annotation tools
Mar 26, 2024 pm 08:20 PM
Text annotation is the work of corresponding labels or tags to specific content in text. Its main purpose is to provide additional information to the text for deeper analysis and processing, especially in the field of artificial intelligence. Text annotation is crucial for supervised machine learning tasks in artificial intelligence applications. It is used to train AI models to help more accurately understand natural language text information and improve the performance of tasks such as text classification, sentiment analysis, and language translation. Through text annotation, we can teach AI models to recognize entities in text, understand context, and make accurate predictions when new similar data appears. This article mainly recommends some better open source text annotation tools. 1.LabelStudiohttps://github.com/Hu
The source code of 25 AI agents is now public, inspired by Stanford's 'Virtual Town' and 'Westworld'
Aug 11, 2023 pm 06:49 PM
Audiences familiar with "Westworld" know that this show is set in a huge high-tech adult theme park in the future world. The robots have similar behavioral capabilities to humans, and can remember what they see and hear, and repeat the core storyline. Every day, these robots will be reset and returned to their initial state. After the release of the Stanford paper "Generative Agents: Interactive Simulacra of Human Behavior", this scenario is no longer limited to movies and TV series. AI has successfully reproduced this scene in Smallville's "Virtual Town" 》Overview map paper address: https://arxiv.org/pdf/2304.03442v1.pdf
Recommended: Excellent JS open source face detection and recognition project
Apr 03, 2024 am 11:55 AM
Face detection and recognition technology is already a relatively mature and widely used technology. Currently, the most widely used Internet application language is JS. Implementing face detection and recognition on the Web front-end has advantages and disadvantages compared to back-end face recognition. Advantages include reducing network interaction and real-time recognition, which greatly shortens user waiting time and improves user experience; disadvantages include: being limited by model size, the accuracy is also limited. How to use js to implement face detection on the web? In order to implement face recognition on the Web, you need to be familiar with related programming languages and technologies, such as JavaScript, HTML, CSS, WebRTC, etc. At the same time, you also need to master relevant computer vision and artificial intelligence technologies. It is worth noting that due to the design of the Web side
Alibaba 7B multi-modal document understanding large model wins new SOTA
Apr 02, 2024 am 11:31 AM
New SOTA for multimodal document understanding capabilities! Alibaba's mPLUG team released the latest open source work mPLUG-DocOwl1.5, which proposed a series of solutions to address the four major challenges of high-resolution image text recognition, general document structure understanding, instruction following, and introduction of external knowledge. Without further ado, let’s look at the effects first. One-click recognition and conversion of charts with complex structures into Markdown format: Charts of different styles are available: More detailed text recognition and positioning can also be easily handled: Detailed explanations of document understanding can also be given: You know, "Document Understanding" is currently An important scenario for the implementation of large language models. There are many products on the market to assist document reading. Some of them mainly use OCR systems for text recognition and cooperate with LLM for text processing.
Just released! An open source model for generating anime-style images with one click
Apr 08, 2024 pm 06:01 PM
Let me introduce to you the latest AIGC open source project-AnimagineXL3.1. This project is the latest iteration of the anime-themed text-to-image model, aiming to provide users with a more optimized and powerful anime image generation experience. In AnimagineXL3.1, the development team focused on optimizing several key aspects to ensure that the model reaches new heights in performance and functionality. First, they expanded the training data to include not only game character data from previous versions, but also data from many other well-known anime series into the training set. This move enriches the model's knowledge base, allowing it to more fully understand various anime styles and characters. AnimagineXL3.1 introduces a new set of special tags and aesthetics
Single card running Llama 70B is faster than dual card, Microsoft forced FP6 into A100 | Open source
Apr 29, 2024 pm 04:55 PM
FP8 and lower floating point quantification precision are no longer the "patent" of H100! Lao Huang wanted everyone to use INT8/INT4, and the Microsoft DeepSpeed team started running FP6 on A100 without official support from NVIDIA. Test results show that the new method TC-FPx's FP6 quantization on A100 is close to or occasionally faster than INT4, and has higher accuracy than the latter. On top of this, there is also end-to-end large model support, which has been open sourced and integrated into deep learning inference frameworks such as DeepSpeed. This result also has an immediate effect on accelerating large models - under this framework, using a single card to run Llama, the throughput is 2.65 times higher than that of dual cards. one
1.3ms takes 1.3ms! Tsinghua's latest open source mobile neural network architecture RepViT
Mar 11, 2024 pm 12:07 PM
Paper address: https://arxiv.org/abs/2307.09283 Code address: https://github.com/THU-MIG/RepViTRepViT performs well in the mobile ViT architecture and shows significant advantages. Next, we explore the contributions of this study. It is mentioned in the article that lightweight ViTs generally perform better than lightweight CNNs on visual tasks, mainly due to their multi-head self-attention module (MSHA) that allows the model to learn global representations. However, the architectural differences between lightweight ViTs and lightweight CNNs have not been fully studied. In this study, the authors integrated lightweight ViTs into the effective